Published on the 08/04/2026 | Written by Heather Wright

Focus beats tools in AI adoption…

AI is delivering real value for a small number of ecommerce businesses in Australia – but for many others it’s simply making busy teams even busier – and not in a good way. According to the 2026 eCommerce Founders report it’s not the tools being used, but how they’re being applied – and whether the business understood where its bottleneck was before it applied AI.

The report is based on ‘insights’ from more than 4,000 eCommerce founders which Australian company Ecommerce Equation has worked with, and draws a clear line between founders who are seeing commercial impact from AI and those who feel increasingly overwhelmed by it.

“Where that understanding is missing, AI simply creates more activity, complexity and noise.”

The report highlights that AI performs best when companies already understand their business constraints. Those seeing real gains are the ones who know exactly which problem they’re trying to solve.

Or as says Jay Wright, Ecommerce Equation founder, says:  “The founders getting real results aren’t the ones doing the most with AI. They’re the ones who knew their business well enough to know exactly where to point it.”

Founders who skip this step tend to deploy AI broadly, without a clear objective or identifying a bottleneck, resulting in more output but little impact on revenue, margin or time saved, a pattern described as  ‘activity without moving the dial’.

In contrast, those who are seeing results are described as starting with a precise diagnosis: A conversion issue on one product, uncertainty in reordering decisions, a slowdown in creative testing or excessive manual operational work. In these case, AI is applied narrowly to the bottleneck and measured against a defined outcome, such as conversion rate, marketing efficiency, time saved or cash conversion speed. In essence, AI doesn’t fix unclear fundamentals; it amplifies existing systems. Where founders already know what ‘good’ looks like in their business, AI accelerates progress. Where that understanding is missing, it simply creates more activity, complexity and noise.

“The short version is this. AI is delivering real value for a small number of founders who have done the diagnostic work first. For everyone else, it’s generating activity without moving the needle.”

Where AI delivers real value: Revenue and conversion

The strongest, most immediate wins documented in the report occur on the revenue side of eCommerce operations. These include conversion rate optimisation, creative production, advertising performance and customer experience.

Lead-side work of getting products in front of the right people and converting are where most brands find their first meaningful wins, the report says, with successful brands using AI to tighten the connection between product and customer with clearer landing pages, tailored ads and a stronger read on what is resonating and the speed to act on it. “The feedback is fast, the impact is visible and the tools are mature enough to act on.”

For those who are getting it right, the report claims the wins are visible and fast, with conversion rates jumping 24 percent in a week from a single tool built around one specific customer problem.

That 24 percent figure relates to Australian apparel brand The Lullaby Club. It identified that a best-selling product fit differently from the rest of the range, rendering the standard size guide ineffective. A custom AI fit-finder was built in Claude for that single product. When it was tested with the 40,000-strong customer community, it achieved a 97 percent sizing accuracy. Within a week, conversion increased by 24 percent and returns fell. With confidence in that project, Lullaby turned its focus to other initiatives including a velocity trends tracker to show how products were selling and trends, using the same data foundation.

“We’re seeing brands go from sub-three percent to 7-11 percent conversion every day by feeding AI the right context about the customer,” the report says of some of the quick wins achieved.

The report also points to growing, if less headline-grabbing, wins on the operational side. Inventory forecasting, purchase ordering and customer service workflows are emerging as areas where AI is beginning to reduce manual effort and uncertainty.

Companies using AI to draft purchase orders, track sell-through rates and flag shifts in momentum are tightening cash conversion cycles and reducing guesswork.

Australian independent apparel brand Dr Moose is one example. The company identified that growth was being constrained its website. Rather than outsourcing work to an agency, she used Claude tools to redesign site UX, introduce bundles and adjust commercial settings herself. Changes previously scoped as a $15,000 web development project were implemented internally, lifting daily revenue from around $600 to $3,000. To get the most from the tools she used ChatGPT to work out what to ask Claude, avoiding burning tokens on trial and error.

Where AI falls flat

The report is equally direct about common failure modes. The most frequent is confusing activity with impact. Those who deploy AI before identifying a real bottleneck often rebuild systems that already work, or chase issues they don’t have.

But the report also notes there are real risks companies need to understand before they go too far down the rabbit hole. “AI will produce data it doesn’t have, confidently and without

flagging it. It too easily gives everyone asking the same question the same answer. And it will sand off the rough edges that make your brand distinct if you let it.”

Those getting the most out of it are the ones who stay in the loop, sense check the output and never let it make the call they should be making themselves, the report notes.

The report leaves little ambiguity about what separates results from noise: AI delivers value where it is applied with intent, against clearly defined constraints with humans remaining closely involved in the outcomes.

Where it is treated as a general productivity layer or a substitute for decision‑making, it tends to add complexity rather than remove it. The implication for eCommerce founders is practical rather than philosophical: AI works best not as a strategy, but as an execution tool, applied deliberately, measured against specific outcomes, and expanded only once it proves its worth.